Catastrophe anonymisation is the removal of direct identifiers from an event dataset. UK GDPR Recital 26 puts truly anonymous data outside the rules, and the ICO tests that with a motivated-intruder question. Where the table stays personal data, Art. 89(1) requires safeguards for statistical use. Flood exposure may also sit behind Flood Re, the scheme set up under Part 4 of the Water Act 2014. anonym.plus marks each identifier on your device.
When this applies
An event dataset ties each loss to a named policyholder and a location. A CAT model needs the peril, the loss, and the geography — but a full postcode names a household. You strip the identifiers and coarsen the geography before the data feeds the model.
How anonym.plus handles it
- Open the dataset in anonym.plus on your device.
- The tool flags names, IDs, and contacts per row.
- Local OCR reads any scanned source sheet.
- Turn the alias map OFF for true anonymity.
- Swap or black out the confirmed identifiers.
- Save the clean table locally.
What you need to provide
- The event dataset (CSV exported to PDF, DOCX, TXT).
- An operator (Redact suits a modelling table).
- The alias map turned OFF so no link survives.
PII & financial identifiers detected
| Category | anonym.plus entity type | Example |
|---|---|---|
| Names | PERSON | policyholder name → [SUBJECT] |
| Identifiers | UK_NINO | national insurance no → [NINO] |
| Financial | MONEY | loss £38,500 → [AMOUNT] |
| Location | LOCATION | loss postcode → [REGION] |
| Dates | DATE_TIME | event date 2025 → [DATE] |
| Contact | EMAIL_ADDRESS | holder@example.co.uk → [EMAIL] |
Compliance achieved
- Aims at the anonymity standard in UK GDPR Recital 26, tested by asking what a motivated intruder could achieve.
- Where the table stays personal data, UK GDPR Art. 89(1) requires safeguards for statistical processing and names pseudonymisation as one.
- Leaves peril, event date, and loss columns whole, including exposure ceded to Flood Re under Part 4 of the Water Act 2014.
- Turning the alias map off removes any re-link route; the run stays offline.
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Limitations & cautions
Recital 26 treats data as anonymous only if no one can re-identify a person. After a named storm or flood the affected streets are often public knowledge, so a precise postcode plus a large loss can single out a household. Coarsen the geography before you publish.
Frequently asked questions
When is an event dataset truly anonymous?
Recital 26 sets the bar at no reasonable means of re-identification. Remove direct identifiers, then coarsen rare location and loss combinations before you decide the bar is met.
Why coarsen the postcode?
A full UK postcode covers only a handful of addresses, and after a named event the affected streets are often reported publicly. Reducing it to a wider region is what makes the Recital 26 standard reachable.
What if I cannot fully anonymise?
Then the table is still personal data and Art. 89(1) applies: use pseudonymisation and access controls, and document the choice.